M.P. Gen. Resources Chap 24

M.P. Gen. Resources Chap 24

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Indicators for Sustainable Management of Plant Genetic Resources: How Well are we Doing? A.H.D. Brown and C.L. Brubaker Centre for Plant Biodiversity Research, CSIRO Plant Industry, Canberra, Australia

Introduction The 20th century has seen an enormous transition in our appreciation of plant genetic diversity. The century began with the rediscovery of Mendel’s laws of inheritance, and through Johanssen the dawning of modern plant breeding. The basis and method for scientific plant improvement were to hand. In addition, the post-Darwinian world saw no short supply of genetic diversity within crop species, nor was such diversity viewed as threatened. Then through the century awareness has grown that genetic resources are indeed limited. With the spread of agricultural development worldwide, local varieties and minor species have given way to modern introduced varieties of major crops. By the mid-1970s, concern for plant genetic resources (PGR) was widespread and efforts to conserve them underway. PGR were generally divided into domesticated populations (landraces, obsolete cultivars, breeders’ populations, modern varieties of crops, genetic stocks) and wild populations (wild plant species especially those related to crops). The dominant strategies were to conserve domesticated germplasm in genebanks ex situ, and wild populations in nature reserves in situ (Frankel and Soulé, 1981). Since 1980, several issues, concerns and forces have emerged to question claims of progress toward adequate PGR conservation (Marshall, 1989). The major ones are:

● National awareness of the value of plant genetic resources has grown, particularly in economically poor but ‘gene rich’ countries in the centres of crop diversity. Since the Convention on Biological Diversity such countries have assumed greater responsibility for the conservation of their own indigenous genetic resources and expect to receive their fair share of benefits from their use. ● The number of accessions in ex situ collections has continued to grow, while their use and maintenance of their viability remain problematic. ● Several hundred crop or wild plant species, previously used by humans, are now classed as Underutilized or Neglected. They are poorly represented in ex situ collections and without increased attention stand to be the main arena of genetic erosion. ● Botanical gardens organizations have sought to take an increasing role in the conservation ex situ of wild species. How their efforts in seed banking of wild species are to be integrated into other PGR conservation measures is an open issue. ● Despite the increase in areas protected for nature conservation, nature reserves generally hold a limited and biased slice of agricultural biodiversity. Many factors (biological, political, economic, amenity) other than concern for wild crop relatives, or even of the utility of wild species determine where such reserves are set

© IPGRI 2002. Managing Plant Genetic Diversity (eds J.M.M. Engels, V. Ramanatha Rao, A.H.D. Brown and M.T. Jackson)

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aside. Just how biased the coverage is is not known. There are very few areas expressly reserved to conserve wild relatives of crops. ● In many countries, farmers, particularly those in marginal areas, continue to grow their own local varieties (Brush, 1995). Yet the stability of such on-farm systems as a conservation strategy in the face of quickening development is not known. ● New genetic technologies, especially DNA sequencing on a larger scale than thought possible, has meant the flowering of molecular systematics and new ways to measure genetic similarity and divergence of plant species and populations. How well are we managing plant genetic resources for sustainable human benefit? This simple question requires objective pointers or indicators as to whether and where the task is being addressed well and where it is not. Governments, industry, scientists and the public require means of measuring progress in this task, and for sounding early warnings of emergencies.

Indicators Purpose and scope Indicators are tools to monitor progress and point to emerging problems. Saunders et al. (1998) define an indicator as a significant physical, chemical, biological, social or economic variable that is measurable in a defined way for management purposes. Indicators that measure the quality of the physical environment, for example, atmospheric CO2 concentration, are relatively straightforward and interpretable. However, suitable indicators for tracking the state of biological resources locally and globally are more difficult to agree upon. In a broad sense, national and international statistics on cropping areas, yields, droughts, plant disease outbreaks, plagues, farm income, agricultural production and trade, even famine, are indirect measures of human wellbeing and indirect indicators of sustainable use of PGR. However, these are only the broadest pointers to policy decisions. Here we limit the discussion to indicators closer to the biodiversity at stake, technical questions and managerial decisions at the level of institutions and researchers.

The developers of indicators for sustainable management of PGR face what seems to be a fundamental and apparently insoluble dilemma. On the one hand, we are aware that the system is a highly complex one in which a great variety of forces (or pressures) can potentially act to threaten PGR. It includes the actions of individual farmers, scientists, breeders, communities, industry, conservation agencies and governments. Consequently, an equally large array of parameters of varied complexity, scale and cost can be nominated as important variables to monitor. On the other hand, while an innumerable array of variables might seem necessary to explain ‘the system’, such a suite will attract no support from users as indicators. There are too many to follow, to interpret and to act upon, and a reductionist approach is inescapable. Deciding on a list of indicators is only the first step. Interpretation of data presents challenges that need prior thought. One intent is to have absolute standards (e.g. a specific number of varieties should underpin crop production in a certain area, or the germinability of genebank accessions should remain above 85%). Alternatively, the intent may be to monitor change over time with specific rates of change deemed desirable or acceptable (a certain number of accessions regenerated per year). Benchmarks or threshold values need to be determined scientifically. In contrast, targets are tools of policy and are specified levels or ranges for the indicators set jointly by groups of stakeholders. Further detailed discussion on the policy interpretation of each indicator lies outside the brief of this chapter.

Biodiversity management As well as for environmental quality, there is an upsurge in interest in developing indicators for conserving biodiversity at the ecosystem, species and gene level. As governments seek to implement the Convention on Biological Diversity, they require indicators to measure progress, to monitor the main human impacts on biodiversity (sustainable development, conservation and use) and to give early warning of any irreplaceable loss. Despite the difficulty of the task, it is clear that experts and conservation agencies in several countries are proposing indicators to encourage and improve the management of biodiversity in nature. Foresters have perhaps led the way in calling for


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Indicators for Sustainable Management of PGR

indicators to monitor the genetic effects of direct exploitation of forests (Ledig, 1992; McKenney et al., 1994; Boyle and Sayer, 1995; Namkoong et al., 1996; Boyle, 2000). Using population genetics theory, Savolainen (2000) considered the basic evolutionary processes generating and maintaining diversity, and discussed heterozygosity of marker genes as a useful indicator of historical effects. A classic example is the contrast between the extremely low values of heterozygosity in Pinus resinosa and the high values in Pinus sylvestris, indicating the lingering effects of bottlenecks in population size of P. resinosa in the distant past. As part of a wider project seeking indicators for national reporting on the ‘State of the Australian Environment’ (the term included both the physical environment and the biodiversity it supports), Brown et al. (1997b) proposed seven indicators to monitor natural genetic diversity in selected indicative taxa. These were: 1. Number of sub-specific taxa; 2. Population size, number and physical location; 3. Environmental amplitude of populations; 4. Genetic diversity at marker loci within individuals and populations; 5. Quantitative genetic variation; 6. Interpopulation genetic structure; and 7. Mating system. Of these, Saunders et al. (1998) integrated the first four into the overall proposal for national biodiversity indicators at all levels. Desirable properties of indicators In attempting to develop indicators for Canadian forests, McKenney et al. (1994) gave as guidelines for the selection of indicators the following criteria. [Ideal indicators] are easy to implement, are based on good experimental design and analysis, do not disturb the system, avoid fads, indicate both process and flows as well as states and stocks, give early warnings, contain some dramatic ‘flagship’ species and other ‘umbrella’ species, target all scales, are participatory for all stakeholders, and have clear specific objectives.

Table 24.1 is a longer wish list of properties of the ideal indicator from the perspectives of the operator of indicators, the manager and the user of PGR, and the wider community. However, it is easier to draw up such a list of ideal properties, and to lengthen it still further, than it is to find indicators

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that satisfy such a list. We consider that the first three items, namely, validity, clarity of interpretation and simplicity in measuring genetic diversity, must be given top billing when assessing indicators.

Potential Indicators According to Genepool and Conservation Strategy McKenney et al. (1994) divided indicators into those that are ‘species-based’, and those that are ‘system-based’. Ferris and Humphrey (1999) called these structural and compositional indicators. Others have used the division into Pressure, Condition or State, and Response. We use the partition mentioned above as two axes of classification. The first axis is the kind of genepool (primary or cultivated versus secondary and tertiary or wild relatives), and the second refers to the conservation strategy (in situ versus ex situ) (Table 24.2).

Primary genepools in situ The state of crop plant diversity actually under cultivation on farms, in pastures or in gardens has been the original focus of the genetic resources movement. It is therefore a natural subject for the development of indicators, particularly to watch for the process of ‘genetic erosion’. The Food and Agriculture Organization (FAO) documentation for the Leipzig technical conference (FAO, 1998) contained a list of possible indicators of genetic erosion of landraces (Table 24.3). These indicators are clearly candidates for our task here, because genetic erosion, or the steady loss of genetic diversity in onfarm agriculture, is perhaps the key ‘pressure’ on the sustainable management of domesticated PGR. Brown (1999) took a different tack and considered variables for the study of genetic structure of landraces that were being conserved on-farm. The approach was based on testing five putative advantages of in situ conservation, and the resulting indicators were numerous and wide-ranging. In Table 24.2 we reduce these and other potential variables into a set of four. Topping the list is the number and frequency of occurrence of distinct landraces of a crop (in a given area). Of course this begs the question of how reliable is the classification and recognition of landraces, and how widespread is the common use of particular names. In some crops, such as sorghum in Ethiopia, a single


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Table 24.1. Checklist of desirable properties for indicators for managing genetic resources (adapted from Saunders et al., 1998). Indicator intrinsic properties Scientifically valid and credible Easy to understand, unambiguous and robust Simple and cheap to assay Use accepted and well-documented methods Cost-effective (i.e. an expensive indicator should yield greater information) Adaptable for use at a range of spatial scales Aggregative (capable of meaningful summation over items and scales) Capable of being monitored easily to show trends over time Managers of PGR Relevant to management objectives and fit in a policy framework Part of the management cycle and not an end in itself Focus on the use of information rather than the gaining of it Render progress evident Kept under review and refined when necessary Users of PGR Developed with all people involved: stakeholders, monitors Reflect an essential, fundamental and highly valued element of the object being monitored Provide early warning of emerging issues or problems Other essential elements for indicator development and use Partnerships between communities, governments, companies and research agencies setting up and running the process and sharing information The provision of adequate resources (time, expertise, funds) A commitment to collect new data Continuing research and development for improving indicators and determining cause and effect

field might be planted to as many as 20 landraces, while in others, such as lucerne in Morocco, a farmer’s variety might not bear a distinctive name, but just be known as ‘local variety’. Breeding system and plant morphology affect the way in which such naming interacts with farmer management of this diversity. Several studies have been made of the reliability of farmer names in reflecting diversity consistently. Remarkable reliability has been found, for example, in farmer recognition of sorghum landraces in Ethiopia (Teshome et al., 1997). Such studies are important in underpinning reliance on names for estimating indicators. Further, if the studies include assay of divergence and distinctiveness for genetic markers for a sample of such landrace populations, we can get estimates of the fundamental levels of polymorphism involved. However, an important point is that names are signals to adaptive or yielding attributes and through them to farmer management strategies. Named populations will be treated in particular ways, almost irrespective of the genetic differences. As such, names, which probably evolve themselves,

affect, if not control, the immediate future of these populations. A variable landrace, bearing a certain name, may be reputed to be flooding tolerant, and planted accordingly, thus setting up selection pressure to emphasize that attribute. Another factor in the equation is the environment where crops are grown. Hence the second area for indicators to address, is a measure of the range of environments that the landraces of a crop species currently occupy. This aspect is not explicit in the FAO list (Table 24.3), but is listed second in Table 24.2. The notion here is that the wider the span of environments that a crop occupies, the greater the adaptive genetic diversity that crop might house. Using survey data on crop occurrence, geographical information systems and multivariate methods may offer ways in which environments can be classified and typified. This would lead to measures of the extent of occupied environments and such measures could be compared over time for changes. Eyzaguirre (unpublished) has suggested this kind of indicator for taro (Colocasia esculenta) in China, a species that is important for food security and has income generating potential.


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Table 24.2. Indicators for sustainable management of plant genetic resources. Genepool

In situ

Ex situ

Primary

Number and frequency of landraces, and area planted to them Environmental amplitude of crop area Durability and evolution of farmer management and farmer selection criteria Security of traditional knowledge

Secondary and tertiary

Distribution in protected areas, that cover the species’ environmental range Population numbers and size, particularly of rare wild crop relatives Gene diversity, divergence and distribution

Number of accessions in the genebank Country distribution of genebanks Coverage in collection of crop diversity Extent of usage and representation in core collections Collection health, accession viability Documentation and evaluation of collection Backup duplication provisions Number and frequency of accessions used Coverage of species range Evolutionary relationships and taxonomic clarity ‘Prebreeding’ activities, including evaluation DNA banks

In measuring sustainable management of crop diversity on-farm, we must recognize that farmer decisions lie at the root of what diversity will be planted. Hence we need to obtain measures of how durable are farmers’ selection criteria and management practices and how they are evolving. For example, populations selected for multiple purposes such as for ease of growth, grain, fuel or fodder straw production, may be more diverse than those cropped solely for sale to the market, particularly when there is market stress on uniformity. Multiple use is also the basis of an indicator for taro where different genotypes and different organs of the plant are put to separate uses (Eyzaguirre, unpublished). The last indicator is to meet concerns about loss of knowledge as to how and why certain species and landraces are grown or used. It also addresses the new demands of benefit sharing. Sustainable management of resources existing in local varieties calls for the creation of mechanisms to secure traditional knowledge. In a sense this activity is parallel to the systems of plant breeders rights that exist in developed agriculture. Monitoring the existence and scope of such systems of protection will be indicative of forces to help encourage the sustaining of diversity on-farm. We therefore focus on four areas, the crops themselves, the environment they occur in, the farmer management practices and the information. Each relates back to the different landrace populations as entities. For this reason, the number of landraces, coupled with their frequency and area

occupied by each landrace forms the fundamental variable for the minimum indicator.

Primary genepools ex situ Since the 1960s, the growth of institutional genebanks that hold accessions as dried seed, in tissue culture, or as living plants in the field has been prodigious. Along with such an investment have come considerable thought, research and experience into how to judge progress in genebanking. Table 24.2 includes some well-established variables (such as viability, documentation, duplication) used in evaluating collections. However, the primary datum is the number of accessions for each crop held in each of the large institutional genebanks. The 1998 report on the state of the world’s genetic resources contains data collected from worldwide surveys. The collections are further divided into whether the material is held in long-term conservation, medium-term accessibility, or indeterminate storage. In several of the larger collections, accessions have been counted twice because they are in both conditions. Indeed, the same report estimates that of the 6 million accessions stored worldwide, between 1 and 2 million are ‘unique’. These figures are perhaps the ‘best’ examples we have of indicators of genetic resources management. They exemplify both the benefits and the problems or pitfalls of making inferences based on


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Table 24.3. Indicators of genetic erosion of landraces as proposed by FAO (1998). Occurrence of landraces Number of landraces Vernacular names of landraces Main distinguishing morphological or agronomic traits Changes in area devoted to landrace cultivation Changes in agronomic practices Indigenous and local knowledge Population diversity of landraces Phenotypic diversity Population size Extent of distribution in a target region Modern varieties Ratio of crop area growing modern varieties to that growing landraces Seed source and distribution mechanisms Promotion of new agronomic practices Reasons for introduction of new varieties Note that the 1999 FAO meeting in Prague on methodology of the World Information and Early Warning System on Plant Genetic Resources defined genetic erosion as ‘A permanent reduction in the number, evenness and distinctness of alleles, or combinations of alleles, of actual or potential agricultural importance in a defined geographical area.’

them. To illustrate this we summarize in Table 24.4 the FAO (1998) estimates of the total number of accessions for the eight main cereal crops and compare these with those give by Holden (1984) in his overview of the situation a decade earlier. The picture is similar for legumes and forages. In nearly all cases there is a doubling of the numbers in collections. If this is true we could certainly infer that the numbers in store cannot keep growing at this rate. It is likely that part of the growth represents collections or samples that were in hand in 1984 but not included in Holden’s total (e.g. for Table 24.4. Estimates of the total number of accessions stored in genebanks worldwide. Holden (1984) Cereals Wheat Barley Rice Maize Oat Sorghum Millet Rye Total cereals Grain legumes Forage legumes Forage grasses

401,500 280,300 212,200 99,700 37,000 91,000 56,000 18,300 1,200,000 185,140 84,200 127,900

FAO (1998) 788,654 486,724 420,341 261,684 155,049 168,550 145,476 27,132 2,454,000 871,577 168,530 240,978

oat). Likewise there could be material that escaped the latest census. The point is, however, that there has been at least a doubling in the size of the formal commitment of the PGR community in numbers of conserved units. Part of this growth may represent the deliberate duplication of material from one country to another (or indeed duplication within a collection in different storage conditions, or in vitro and in the field). This has come about from policies of insurance backup storage, repatriation, or introduction of large collections to new areas. Whatever the degree of planned duplication and of inadvertent redundancy, each accession is a managed unit, kept and recorded as distinct. For example, it is of interest to know that a collection has a total of 80,000 accessions made up of 40,000 in long-term store and the same 40,000 in medium term. The basic figure is the total number of accessions stored. This statistic can be judged and modified with values for the remaining indicators in this group. The first of these asks how well the material in genebanks covers the existing crop diversity. This may be hard to assess, because it requires knowledge of what is in hand and what is not. Yet the filling of gaps has been stated often as a need, and various methods of identifying gaps are available to do this. Next is the question of usage, which might be measured by the number of samples dispatched per


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year. Again this figure can be misleading and likely to overestimate usage because of requests or responses in excess of needs. Equally, however, the number of appearances in the pedigrees of cultivars is a vast underestimate of usage. It ignores the base screening population from which particular selections were made, or the extent of sampling on which biological research was conducted. The proportion of a collection that forms the basis of a core collection is another indicator of sampling usage. In a recent worldwide survey of core collections, Brown and Spillane (1999) found that the core collection procedures have been adopted for a wide range of crop types. However, the adoption rate was apparently greater in medium-sized germplasm collections, and the larger collections have so far not been subject to such sampling principles. The other suggested indicators are straightforward and familiar, and deal with the state of the germplasm collection. Here we can build on the international experience in the monitoring of genebanking. The International Plant Genetic Resources Institute (IPGRI) and FAO (FAO and IPGRI, 1994) have recently published standards for genebank management that provide benchmarks for indicators. Holden et al. (1993) have mapped out in detail how such variables could be combined into a ‘score’ to attach to each accession. The average over the whole collection could function as an indicator. It is interesting to consider why such proposals were not widely adopted as a way to lobby funding bodies for more resources to redress problem areas. Perhaps the risk was too great of unfair public comparisons between genebanks that ignored radically different levels of resources. This history shows how important partnerships will be in formulating and using indicators that will enjoy wide support (Table 24.1). Monitoring the health of collections, particularly of field genebanks, and assessment of accession viability are essential housekeeping functions. The FAO (1998) overview inevitably found a diverse picture on these parameters, and particularly stressed the growing backlog of samples for regeneration. Documentation and evaluation also inevitably but perhaps less critically, were also variable across the spectrum of collections. These activities may never be totally complete and perhaps a more helpful indicator is a measure of the annual effort being devoted to them, rather than an estimate of the proportion of the task not done. Once again the overall indicator that captures most of the genebanking effort is the total number

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of accessions of a crop conserved in a genebank. This could primarily reflect the number to which an institution is committed to conserve. The secondary indicators come into play in assisting in improving the growth and management of that collection, and hence its value and sustainability.

Secondary genepools in situ From one of the more traditional modes of conserving agricultural plant genetic resources, we turn to the other and polar opposite, namely the conservation of wild related species in nature reserves. The first question to consider is why emphasize wild species that either are used directly, or are wild relatives of crops? After all, modern molecular technology gives access to the ‘quaternary’ genepool, that is without limit. Should our thinking be broader to encompass other forms of biodiversity than higher plants, such as fungi, at the level of ecosystems? However, we argue that the PGR community has a special concern for and focus on the wild relatives of domesticated plants. Their roles as alternative hosts in coevolutionary relationships, and their long history as proven sources of useful genes assure them of that focus. Indeed they are natural ‘flagship’ species, and have proved important in achieving political support for conservation activity in the cases of Zea diploperennis in Mexico and Triticum dicoccoides in Israel (Frankel et al., 1995), and the Antalya Gene Management Zone in Turkey (see Tan and Tan, Chapter 19, this volume). But to judge progress and give early warnings we need a broader view than the few celebrated cases. One problem is the number of species to consider, presumably at least an order of magnitude higher than their related crops. As well, there are two attitudes to the diversity in wild relatives. On the one hand some (e.g. Marshall, 1989) have pointed out that for many crops, many areas of the world are colonized by certain wild relatives of crops (e.g. wild Avena species), and that such cases would not merit monitoring. On the other hand, others have argued that highly specific ecotypes or populations have proven value (e.g. the sources of certain crown rust resistances in Avena spp. in Israel), and these sometimes weedy populations collected beside farmers fields are endangered and should be monitored. With the emergence of IUCN red book lists, it becomes possible to get an overview of the situation at least at the species level. The task at the national


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level is to consider the indigenous species of genera that have domesticated or economically useful species, decide which species are rare and threatened, and for those obtain estimates of population number and sizes. A second approach is to consider which crop-related wild species are present in nature reserves and other protected areas and which are not. Of those omitted, the question to check is whether their population distribution, number and sizes are such that they need no conservation action. Table 24.5 is an example of what can be done with such lists. It lists the genera related to economic plants that are included in Briggs and Leigh’s

(1996) authoritative survey of the conservation status of rare or threatened plants of Australia (ROTAP), and the number of native species that belong to each category. Of the crop genera listed, appreciable proportions of wild species are of conservation concern. Over half of these were too ‘poorly known’ to classify as to their endangerment status. While some are known to be in reserves, only about 20% of species related to field and vegetable crops and ‘at or likely to be at risk’ could be checked off as adequately reserved. The situation for eucalypts is perhaps most indicative. They are big plants, easy to see and well

Table 24.5. The number of Australian native species congeneric with or closely related to crops, and the number of those species in various conservation categories. Genus

Australian Extinct Endangered Vulnerable

Field Crops Glycine c. 25 Gossypium 17 Sorghum 17 Nicotiana 20 Amaranthus 27 Cajanus 11 Corchorus c. 40 Vegetables Solanum c. 100 Dioscorea 5 Ipomoea 50 Apium 4 Oils, fruits, nuts, spices Eucalyptus c. 800 Melaleuca c. 250 Macadamia 7 Ficus 40 Syzygium c. 80 Cinnamomum 5 Piper 8 Musa 3

1

1 1

13 1

1a

Rare Poorly known In reserves 1 2 1 1

1 3

4

1 1

2

68 2 4

98 9 2

4

13 2 1 1

4 4 1 3 1 1 5

3 3

6 1 2

5

80 26

151 16 5

5 2

1

2

1

12 2 1 1

Summarized ROTAP definitions (following Briggs and Leigh, 1996): Extinct, not collected or otherwise verified over the past 50 years despite thorough searching. Endangered, in serious risk of disappearing from the wild within 10–20 years if present land use and other threats continue to operate. Includes populations too small to be assured survival even if conserved. Vulnerable, not presently endangered but at risk over a longer period (20–50 years) under current conditions or because it occurs on land whose future use will place it at risk. Rare, taxon that is rare in Australia but does not have an identifiable threat. Small number of large populations in a restricted area or small populations over large areas, or combinations of the two preceding conditions. Poorly known, suspected to belong to one of the above categories. Crop genera not listed: Oryza, Linum, Vigna, Chenopodium, Cucumis, Citrullis, Abelmoschus, Alocasia, Citrus, Prunus, Olea, Rubus, Myristica. aMusa fitzalanii F. Muell. Daintree’s River banana, presently known only from the type specimen.


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studied, yet 10% of species are probably of conservation concern and their vulnerability too poorly known to classify. Of the 259 species of conservation interest, only 151 are adequately represented in reserves. At the other extreme the situation for crop genera for which no species are listed, might imply that their species are indeed at no risk (e.g. Oryza), or that they have escaped attention. Our suggested indicators (Table 24.2) exploit the general tendency for genetic diversity to increase with increasing population size (Young et al., 1996). Area occupied could be a surrogate for size. Another contender is population density, because density may often be easier to measure than population size to which it is probably related. However, as Gram and Sork (1999) found, density can also be an indicator of habitat quality. In their study, populations with small densities had different genotypes than those with high densities, and thus they recommend choosing populations to represent a range of densities. Another possible approach borrows from that of ecosystem conservationists who have used geographic environmental data to partition areas and select areas for reservation that represent environmental heterogeneity for the species concerned (e.g. Belbin, 1993). In assessing collecting priorities among alleles, the 2 × 2 classification of alleles based on their population frequency (common versus rare) and distribution among populations of a species (widespread versus localized) has proved useful. In a parallel manner, Murray et al. (1999) have classified species based on their population sizes (abundant versus sparse) and geographic distribution in a given area (everywhere versus somewhere, or sometime). They sought life-history characteristics that would be indicators of different kinds of rarity among species, and hence vulnerability to loss. In our case, the number of wild related species for which such classifications are possible from existing data indicates our progress in predicting vulnerable genepools. As before, interpretation of basic data on occurrence, distribution and reservation in protected areas would be much more meaningful with genetic and systematic studies of the population genetic structure of these species. Evidence of cryptic genomic diversity, subspecies or unrecognized species such as have come to light in perennial Glycine species in Australia, or evidence of highly non-uniform levels of diversity in geographic patterns (see Schoen and Brown, 1991) are important pointers to improving reservation strategies.

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Secondary genepools ex situ The final cell of Table 24.2 concerns indicators for the sustainable management of accessions of wild related species in ex situ collections. The primary, long-established reason for such samples is to have them at hand for study and use in breeding (Frankel and Soulé, 1981). Hence, except for the indicator dealing with coverage, the indicators we suggest have a strong flavour of measuring actual use. The primary indicator is the number of different accessions (of each of the relevant wild species in a collection) actually used in research or breeding, and the frequency of such use in a given time interval. These could be computed from statistics on requests, or from surveys of the literature reporting materials used in research as done by Dudnik et al. (2001). As a numerical example, Table 24.6 contains some measures of the pattern of use for the CSIRO collection of indigenous relatives of Gossypium over the last few years. Although the numbers are very small, they illustrate ways to track the use of diversity with indicators. The data are for dispatches from the genebank in answer to requests, for accessions used in first hybrids with either diploid or tetraploid cottons, and used in research crosses among the wild species themselves. Since indicators are meant to be comparative, the intent here is to compare usage of the three genome groups of species: the subtropical C-genome (two species), the tropical G- (three species) and the highly interesting K-group (12 species) that come from the Kimberley region of Western Australia. The latter are rare and very difficult to handle in a genebank. Simply getting seed is a challenge in many cases. From the basic frequency distribution of number of accessions used once, twice, three times, etc., we compute the total number of different accessions used (richness); and the coefficient of variation (CV) of the frequency of use (evenness). To make the figures comparable, the richness values in the table are adjusted to a total usage of 30 by resampling procedures. The evenness figures are transformed to a negative exponential. This means that complete or maximum evenness, which would be identically the same frequency for all accessions used gives a CV of zero and a value in the table of 1.0. Evenness values on this scale range from zero to one, with higher values being more desirable, other things being equal. The data point to the effect of practical limits on using the diversity in the K-group in dispatches.


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Table 24.6. Numerical example: Patterns of usage in germplasm shipments and in hybridization research of the CSIRO collection of indigenous Gossypium species. C-genome Number of species in the genome group Number of accessions in the collection (June 2000) Number in long-term store

2 154 56

G-genome 3 228 112

K-genome 12 81 15

Dispatches Number of samples sent on request Number of different accessions sent Richness (for a total of 30 samples) Evenness (exp[-CV of use]) SW Information Index (SE)

45 31 18.4 0.63 3.34 (0.07)

59 45 21.2 0.66 3.73 (0.05)

64 27 16.4 0.54 3.12 (0.07)

Hybridization with cotton (4X or 2X) Number of cross combinations attempted Number of accessions used as parents Richness (for a total of 30 crosses) Evenness (exp[-CV of use]) SW Information Index (SE)

32 12 10.4 0.66 2.4 (0.07)

32 8 7.6 0.69 2.0 (0.06)

100 33 18.4 0.59 3.4 (0.05)

Hybridization among wild accessions Number of cross combinations attempted Number of accessions used as parents Richness (for a total of 30 crosses) Evenness (exp[-CV of use]) SW Information Index (SE)

68 25 15.8 0.55 3.05 (0.07)

33 11 9.5 0.58 2.25 (0.09)

72 81 17.8 0.46 3.31 (0.08)

Richness, the number of different accessions in the total effort, standardized to a given size by geometric resampling procedures (Brown, 1989). Evenness, coefficient of variation of the frequency of accession use. SW Information Index, Shannon-Weaver Information Index, combining both richness and evenness (Hutcheson, 1970).

On the other hand, a richer sample of K-accessions has been used in crosses while the effort in the Ggenome has been highly concentrated. There are sound reasons for these trends, especially the scientific novelty and importance of the K-crosses, but the point to make here is that statistics to track these patterns are useful in crosses as indicators. Other factors that affect usage in crosses in this case of Gossypium research include rate of success, coverage of the species range, presence of useful traits, ease of growing and abundance of flowering and seeding. How can we measure the adequacy of coverage of diversity in nature by the samples in hand? What intensity and how many samples per species in total should be the target? Sampling benchmarks are already much debated in the literature on genetic resources. They vary widely depending on the kind of species (crop, wild herb, forest tree), the abundance of the material (scarce or plentiful), the purpose of the sample (locally common versus species rare alleles) and the assumptions of the authors. Here we simply want to stress that a sampling of

the complete geographic range of each wild species is a major goal. An important area that commands much current research attention is the study of species relationships and development of molecular phylogenies. Appraising and counting such studies, although potentially involving heated debate, could indicate how well we are coming to know the heritage of crop genetic diversity, and evolution under domestication. The other main area of endeavour for wild relatives concerns ‘prebreeding’ activities. These are research attempts to make the genetic resources in genepools distant from breeders’ populations, more available to breeders. Examples are the development of near-isogenic lines from wild species (e.g. barley) or the development of hybrid populations for molecular mapping of desirable traits and linked markers for manipulating traits in breeding programmes. Summaries of the number of lines, mapping populations and traits developed for each crop would provide an instructive overview of the penetration of wild genetic resources into crop improvement.


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A tool of potential importance is the development of collections of DNA samples in glacie from wild species (see Frankel et al., 1995, for discussion). If readily available, this kind of material could significantly expedite research, and test hypotheses. Such research may lead to more efficient use of living samples, even if it is not the direct source of useful genes. As for any germplasm collection, the size, composition, quality of accessions and documentation, and actual usage of DNA banks all need monitoring. Presently DNA samples in glacie form an adjunct method, rather than replacing other conservation methods and, as such, may be themselves evidence of the usage of ex situ wild collections, to which they are linked.

Role of Newer Molecular Techniques in the Development of Indicators A primary aim of this volume is to map out the future role that new technologies can take in managing PGR. In concert with this aim, we here ask what established and emerging molecular techniques might offer in devising, implementing or improving indicators for sustainable management of PGR. Molecular techniques give the power to monitor genetic variation right at the elemental level of DNA sequences. Starting with the introduction of isozymes, there has been an explosion in the technologies available for directly assaying genetic differences among organisms. It is now possible to compare organisms from the genome level (using for example fluorescent in situ hybridization (FISH) and genomic in situ hybridization (GISH)), down to the level of single nucleotides (DNA sequencing and single nucleotide polymorphisms (SNPs)). Because the genome is assayed directly, these new technologies circumvent the often poor correspondence between morphological and genetic diversity in crop species. Thus, in theory they could increase the validity and credibility of indicators by providing markers that offer greater clarity of interpretation. The immediate and obvious benefit is the flexibility and precision by which genetic diversity can be assayed. Marker systems can be tailored to specific organisms to accommodate differences in breeding systems and relative levels of genetic diversity, and can be scaled depending on the number of accessions to be screened, how many loci are needed, and which sequences in the genome are to

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be sampled. Furthermore many anonymous DNA markers (e.g. randomly amplified polymorphic DNA (RAPDs), restricted fragment length polymorphisms (RFLPs), amplified fragment length polymorphisms (AFLPs)) can be drawn from genomic maps guaranteeing that genetic diversity assays evenly sample the genome. With sequence tagged sites (STSs) developed from expressed sequence tags (ESTs) it is even possible to use expressed genes specific to life history stages, rather than anonymous sequence differences to assay genetic differences among accessions. Because database comparisons can often identify the functional product of an EST, the genebank manager not only gets an indicator of genetic diversity and relationships among accessions but an increase in the informational content of the sampled accession. There are clear benefits to the greater use of these more precise measures of genetic variation. Equally clearly, they are costly in human and financial resources. They can only be employed in a limited number of collections. Therefore, the selection of which species and which samples is crucial. Since the aim is to obtain the maximum amount of useful information from a limited sample, the use of core collections is an obvious approach. Core collections are designated using all the data available, to make their entries representative of genetic diversity. The basic procedure is to recognize groups of related or similar accessions within the collection, and sample from each group. DNA sequence analysis provides the opportunity to measure how different these empirically derived groups are, and test for relationships between them. Here is a fundamental gain in genetic knowledge, not only to prove that two individuals or gene copies differ, but to be able to place them in a phylogenetic hierarchy of relationships, based on recency of a shared ancestor. Once this is done, the phylogenetic diversity of the collection can be estimated (Crozier, 1997). Calculating the phylogenetic diversity of a collection allows PGR managers to extend and improve core collections of secondary and tertiary genepools. Maintenance of these wild related species is often problematic relative to primary genepool accessions (Brown et al., 1997a). In speciose groups, maintaining large unchecked collections of every related species is simply not feasible. Phylogenetic diversity measures can be used to identify a subset of related wild species that maximizes the genetic information content of the collection (Crozier, 1997).


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A case in point would be the wild Australian cotton (Gossypium) species (Brown and Brubaker, 2000). Molecular phylogenetic analyses identified three main lineages among the 17 species; lineages that are now recognized as distinct genomes. The recognition of these three evolutionary lineages is a key variable in three areas: (i) sources of agronomically useful traits; (ii) ability to be incorporated into cotton breeding programmes; and (iii) risk assessment of transgene escape from genetically modified cotton cultivars (Brubaker et al., 1999). In all three areas, the phylogenetic topology has proved to have predictive value and allows the identification of indicator species for each lineage. Equally important, the phylogenetic topology allows germplasm managers to identify high priority species for germplasm further collection and maintenance in what is a difficult group to manage.

Towards both Richness and Balance Up until now, the pursuit of diversity ‘richness’ might be seen as typifying the prevailing philosophy of PGR. Sampling and conservation strategies have sought to maximize the diversity of collections mainly in terms of the total numbers of different genetic entities or types, be they alleles, genotypes or clones. Richness has been the guiding

concept of diversity that has shaped much of the thinking. Such a view of diversity is straightforward. The problem with ‘richness’ from a managerial point of view is that richness is a function of numbers. Larger collections and populations will have more genotypes. There is no evaluation of effort, no setting of priorities competitively. If richness is the dominating indicator, there is no check on growth, nor a check against bias or imbalance in a collection. Large numbers of individuals close at hand can readily be sampled to bolster the number of genotypes, which necessarily must increase merely by enlarged numbers, although inefficiently. There are many examples of this problem in wild species. Our collection of perennial Glycine species began as moderate numbers of accessions of the species near to hand in south-eastern Australia. In later phases it has become clear that the high species diversity is in the monsoonal areas of northern Australia and particularly the remote Kimberley district. Because of ease of access, the collection is biased in numbers to populations near at hand. The same story holds for the wild Australian Gossypium species, which also have striking diversity in the remote north-west. Ideally our collections should be more balanced. Table 24.7 gives a comparison of the kind of questions that are either dominated by the richness

Table 24.7. Comparison of typical questions and perspectives from the previous period of emphasis on ‘richness’ with those in the new era of ‘balance’.

Genetic erosion

Germplasm collections

Clonal species

Richness

Balance

Does loss of an allele or clone have to be complete to constitute genetic erosion? Should we be concerned with the loss of any allele from a species? Have we collected and conserved all alleles and genotypes and maintained all accessions? Is richness maximized? Are all clonal genotypes growing in a secure field genebank and in vitro?

How can we increase the evenness in frequency of use of genotypes, varieties and crops?

Wild relatives

Are all wild related species collected and conserved?

In situ conservation

Has a full description of all the genotypes and all the forces been made to ensure conservation of all?

Are collections organized for ease of use? Has collection evenness improved, by discarding redundancies, gap filling, etc.? Have field genebanks been brought to manageable size and duplicated to ensure they are not lost due to catastrophes? Are structured representative samples of wild relatives on hand for study and use? Are programmes of participatory plant breeding and improvement in place?


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or the balance in approach. We contend that what is now needed is the other concept of point diversity, namely the evenness of frequencies of types. The concept here is that when two items are drawn from a collection or from an assembly of populations they will differ with appreciable probability. The discussion of Table 24.2 gave primacy to data that have both numbers and frequencies of types. These frequency distributions provide the basis on which both richness and balance can be computed. One possibility for a combined index, admittedly somewhat abstruse, is to compute the Shannon-Weaver Information Index, which brings together both richness and evenness. The relative unfamiliarity of such an index and its dependence on the kinds and extent of the basic data, however, work against its adoption, but we believe this is the direction in which we should head. The next challenge for improving balance is to incorporate measures of divergence such as phylogenetic distance, as outlined above. Ideally we wish to measure progress by the sustained retention of a large number of types (richness), all in appreciable frequencies (evenness) and covering a wide spectrum of diversity (phylogenetic divergence). Such measures still do not address any parameters of differential value of types; which are useful alleles and which are not, etc. Should we hand the search for indicators over to the economists? There may be arguments for doing that, as economic value is likely to be a principal factor in determining which fraction of biodiversity will survive. However, we are challenged to sustain PGR despite the pressure of market forces, and indicators that focus on the diversity itself are essential in this process.

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Conclusions The 20th century leaves us with a challenging and essential task: the sustainable management of our physical and biological resources. An indicator is a significant physical, chemical, biological, social or economic variable that is measurable in a defined way for management purposes. For plant biodiversity, indicators are needed at the levels of communities, species and genes. This last is the most difficult, and yet the most important. Many measures are plausible, ranging from the number of varieties of a crop species and the area patterns of their planting in situ, or the number of distinct accessions in genebanks ex situ, through to measures of DNA sequence and genome diversity among populations. They differ in cost, precision and scale of application. Modern technologies have roles in the devising of structured sampling strategies, and the more accurate measuring of population and species relationships. The phylogenetic framework will be an important tool in assessing priorities for action. These approaches will help to make both the collections of PGR, and their conservation and use, richer and more balanced in the coming century.

Acknowledgements This paper was completed while AHDB was a visiting research fellow at the Department of Systematic Botany, University of Osnabrueck and honorary research fellow of IPGRI in Rome. AHDB thanks in particular Drs Toby Hodgkin, Jan Engels, Devra Jarvis, Pablo Eyzaguirre and Herbert Hurka for comments on the manuscript.

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